Cardiovascular disease is a major cause of fatalities. Cardiac electrophysiological (EP) signals are used to diagnose and characterize patient electrophysiological pathology, such as atrial fibrillation and myocardial ischemia (MI). Usually, surface electrocardiograph (ECG) signal and intra-cardiac EP signal analysis based on waveform morphology and time domain parameters is employed for cardiac arrhythmia detection and characterization, involving determining P wave morphology changes, R-R wave time intervals and analyzing heart rate variability, for example. However, there is a lack of a precise and reliable method for categorizing electrophysiological characteristics based upon heart tissue analysis and diagnosis.
Some known research studies describe tissue impedance based analysis, such as for heart evaluation for use in a heart tissue ablation procedure and cardiac arrhythmia discrimination. However, known tissue impedance analysis methods typically focus on calculation of a single EP impedance characteristic based on an external stimulation pulse. Known methods suffer from introduction of electrical noise into EP signals as well as from current and/or voltage leakage that may impair patient safety. Known systems typically employ an external energy source to induce stimulation of a heart and derive myocardial tissue impedance and tissue electrophysiological characteristics. However, this stimulation may cause change to heart tissue electrophysiological characteristics, potentially resulting in patient safety impairment. Precision and reliability of impedance measurement and analysis in known systems is affected by dynamic variation of external stimulation signals and may vary from patient to patient. Additionally, known corresponding clinical methods fail to address multi-channel intra-cardiac impedance mapping and pattern analysis for a cardiac tissue and heart circulation system.
Known current signal processing systems use intra-cardiac electrograms to analyze cardiac arrhythmias, such as Atrial Fibrillation (AF) and Ventricular Fibrillation (VF) but lack diagnosis accuracy and reliability. Although anatomical structure and geometry models may be used by some known medical devices, these models lack precision and reliability in localizing malfunctioning tissue, determining heart arrhythmia severity and life-threatening event timing, especially of a multi-site reentrant mechanism cardiac function. Intra-cardiac electrophysiological signals (ICEG) are used in analyzing and characterizing cardiac pathology and arrhythmias. However, known medical devices fail to characterize tissue status or indicate an underlying cause of an arrhythmia event. A system according to invention principles addresses these deficiencies and associated problems.